Model-Based Electrochemical Estimation and Constraint Management for Pulse Operation of Lithium Ion Batteries

By Kandler A. Smith, Christopher D. Rahn, Chaoyang Wang. IEEE Transactions on Control Systems Technology, 2010

339 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/dc6f01b705931705544945fa6a60ec2aad0e6450

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Citations in the corpus

State of charge estimation of a lithium ion cell based on a temperature dependent and electrolyte enhanced single particle model (2015, methodology): “[15,16] develop a 7th order isothermalmodel in state variable form using residue grouping that”
A survey of mathematics-based equivalent-circuit and electrochemical battery models for hybrid and electric vehicle simulation (2014, positive): “Other methods, including the Chebyshev polynomial method [77, 78], the residue grouping method [79, 80], proper orthogonal decomposition method [81], and Pad´e approximation [82] have also been used to derive reduced-order models for Li-ion batteries.”
State of Charge Estimation for Lithium-Ion Battery Based on Nonlinear Observer: An H∞ Method (2017, methodology): “For instant, the ordinary KF is used to deal with simple and linear battery models [6].”
State estimation of lithium-ion cells using a physicochemical model based extended Kalman filter (2018, methodology): “The work of Hu et al. [15] presents a variety of different ECMs and the reader is referred to this publication for more profound information.”
Battery State Estimation for a Single Particle Model With Electrolyte Dynamics (2017, methodology): “Examples include spectral methods with output error injection [25], residue grouping with Kalman filtering [26], semiseparable structures with an EKF [27], discrete-time realization algorithms with an EKF [28], and composite electrodes with nonlinear filters [29].”
Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles (2018, methodology): “Then an extended Kalman filter (EKF) has been employed to build a modelbased SoC estimator with this simplified model [45].”